When you mentor and advise multiple technical teams and move financial technologies forward, it's a big challenge with big impact. You were made for this.
As a Senior Lead Software Engineer of Software Engineering at JPMorganChase within the Consumer and Community Banking Technology Team, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm.
Job responsibilities
- Lead a highperforming engineering team building and operating cloudnative data platforms that ingest, process, and serve largescale batch and streaming data.
- Own endtoend delivery for data warehousing and multiterabyte to petabytescale migration initiatives, ensuring reliability, performance, security, and cost efficiency.
- Provide technical leadership across Java, Python, Spark, Snowflake, and AWS, while driving strong Agile practice, CI/CD automation, and operational excellence.
- Foster a culture of ownership, collaboration, psychological safety, and continuous learning.
- Own multiworkstream roadmaps plan releases, define milestones, track progress, and remove blockers to hit scope, schedule, and quality targets.
- Create detailed estimates and work breakdown structures, manage dependencies, risks, and stakeholder expectations.
- Define and evolve data platform architecture for batch and streaming use cases (eventdriven, microservices, warehouse patterns).
- Lead largescale data migration (onprem to cloud), data profiling, reconciliation, lineage, quality (e.g., deduplication, schema validation), and backfills.
- Define SLAs implement monitoring/alerting lead incident response, root cause analysis, and continuous improvement.
- Contribute to team culture of diversity, opportunity, and respect.
Required qualifications, capabilities, and skills
- Hands-on practical experience in system design, application development, testing and operational stability and CI-CD process.
- Hands-on practical experience in developing spark-based Frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark Core & Spark Streaming.
- Proficient in coding in one or more Coding languages - Java or Python
- Experience building Data Warehouse platform.
- Cloud implementation experience with AWS including:
- AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Airflow (or) Lambda + Step Functions + Event Bridge
- Data De/Serialization: Expertise in at least 2 of the formats: Parquet, Iceberg, AVRO, JSON
- AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager
- Experience in Snowflake and Databricks.
- Experience in Gen AI skills.
Preferred qualifications, capabilities, and skills
- Experience working at code level
- In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience preferably AWS.
